Chemical Similarity Searching
نویسندگان
چکیده
منابع مشابه
Chemical Similarity Searching
This paper reviews the use of similarity searching in chemical databases. It begins by introducing the concept of similarity searching, differentiating it from the more common substructure searching, and then discusses the current generation of fragment-based measures that are used for searching chemical structure databases. The next sections focus upon two of the principal characteristics of a...
متن کاملWeighted Superstructures for Chemical Similarity Searching
Chemical similarity searching forms an important part of the virtual screening process. In this study, we present a graph-based matching method that assembles the target query graph from a number of active molecules. We apply both a weighted and an unweighted maximum common subgraph algorithm to measure the similarities between all molecules in three different data sets and samples of generated...
متن کاملChemical Similarity Searching with neural graph matching methods
The thesis examines three novel structural similarity methods that employ a network of simple auto-associative neural networks for storing structural information about databases of molecular graphs. This information can be used to discover similarities from a query graph to any of the graphs in the model database. The fast learning and recall ability of the neural network facilitates efficient ...
متن کاملEfficient searching and annotation of metabolic networks using chemical similarity
MOTIVATION The urgent need for efficient and sustainable biological production of fuels and high-value chemicals has elicited a wave of in silico techniques for identifying promising novel pathways to these compounds in large putative metabolic networks. To date, these approaches have primarily used general graph search algorithms, which are prohibitively slow as putative metabolic networks may...
متن کاملChemical similarity searching using a neural graph matcher
A neural graph matcher based on Correlation Matrix Memories is evaluated in terms of efficiency and effectiveness against two maximum common subgraph (mcs) algorithms. The algorithm removes implausible solutions below a user-defined threshold and runs faster than conventional mcs methods on our database of chemical graphs while being slightly less effective.
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ژورنال
عنوان ژورنال: Journal of Chemical Information and Computer Sciences
سال: 1998
ISSN: 0095-2338
DOI: 10.1021/ci9800211